Real-time video streaming has been widely used in the fields such as real-time monitoring and intelligent transportation to provide real-time information for command and judgment. In recent years, lots of unmanned aerial vehicle (UAV) application are proposed. For example, the live streaming or image captured using UAV plays an important role in the fields of application such as geomorphological observation, pollution monitoring, and disaster scenes. Real-time video can help the user to make a judgment at the first time, to correct of flight route, or to modify the direction of the camera. Therefore, real-time video streaming is expected to play an essential role in the fields of application exemplified above.
However, existing video streaming sources (such as surveillance camera, mobile phones, or sport video recorders) all have their restrictions in the field of view (FOV). If the target monitoring area could not be covered by the FOV of one single camera, multiple cameras or UAVs will be applied at the same time t. Since each camera is set at different location with different angle, how to monitor all camera at the same time is very difficult. With the video stitching technology, the vision of all camera can be aggregated as one single video streaming, greatly simplifying the operation of monitoring. Since the contents of multiple video sources can be viewed through one single image, the efficiency of monitoring can be greatly increased and a large amount of labor can be saved.
Video stitching requires heavy computation power. The more the video sources, the larger the amount of computation is required. When a large number of cameras or UAVs are used, the huge computation time leads to a serious video delay.